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Unsupervised data classification using improved biogeography based optimization

Author

Listed:
  • Avinash Chandra Pandey

    (Jaypee Institute of Information Technology)

  • Raju Pal

    (Jaypee Institute of Information Technology)

  • Ankur Kulhari

    (Jaypee Institute of Information Technology)

Abstract

Unsupervised data classification (data clustering) is one of the mostly used data analysis methods which groups the unlabeled data into identical clusters (groups). Classical clustering methods do not perform effectively while clustering high dimensional datasets viz micro array datasets. Therefore, a novel clustering method based on Biogeography based optimization is proposed to extend the capabilities of traditional clustering methods. Performance of proposed method has been tested on the four micro-array datasets. Experimental results validate the effectiveness of proposed method.

Suggested Citation

  • Avinash Chandra Pandey & Raju Pal & Ankur Kulhari, 2018. "Unsupervised data classification using improved biogeography based optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(4), pages 821-829, August.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:4:d:10.1007_s13198-017-0660-2
    DOI: 10.1007/s13198-017-0660-2
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